the study. C.S.S. and L.S. have declared conflicts of interests; the remaining co-authors have no conflicts of interests to declare. Trial registration number Not applicable.Background Infertility is an important side effect of treatments used for cancer and other non-malignant conditions in males. This may be due to the loss of spermatogonial stem cells (SSCs) and/or altered functionality of testicular somatic cells (e.g. Sertoli cells, Leydig cells). Whereas sperm cryopreservation is the first-line procedure to preserve fertility in post-pubertal males, this option does not exist for prepubertal boys. For patients unable to produce sperm and at high risk of losing their fertility, testicular tissue freezing is now proposed as an alternative experimental option to safeguard their fertility. Objective and rationale With this review, we aim to provide an update on clinical practices and experimental methods, as well as to describe patient management inclusion strategies used to preserve and restore the fertility of prepubertal boys at high risk of fertility loss. Search methods Based on the expertise of the participating centres and a literature search of the progress in clinical isk of fertility loss. Study funding/competing interests The work was funded by ESHRE. None of the authors has a conflict of interest.Study question Can the grade of ascites, haematocrit (Ht), white blood cell (WBC) count and maximal ovarian diameter (MOD) measured on Day 3 be used to construct a decision-making algorithm for performing or cancelling embryo transfer in patients at high risk for severe ovarian hyperstimulation syndrome (OHSS) after an hCG trigger? Summary answer Using cut-offs of ascites grade&gt;2, Ht&gt;39.2%, WBC&gt;12 900/mm3 and MOD&gt;85 mm on Day 3, a decision-making algorithm was constructed that could predict subsequent development of severe OHSS on Day 5 with an AUC of 0.93, a sensitivity of 88.5% and a specificity of 84.2% in high-risk patients triggered with hCG. What is known already Despite the increasing popularity of GnRH agonist trigger for final oocyte maturation as a way to prevent OHSS, ?75% of IVF cycles still involve an hCG trigger. Numerous risk factors and predictive models of OHSS have been proposed, but the measurement of these early predictors is restricted either prior to or during the controlled ovarian stimof late OHSS. Study funding/competing interests NHMRC Early Career Fellowship (GNT1147154) to C.A.V. No conflict of interest to declare. Trial registration number N/A.Study question Is it feasible to undertake a randomised controlled trial to establish whether surgical removal of endometrioma or not, improves live birth rates from IVF? Summary answer A randomised controlled trial (RCT) comparing surgery versus no surgery to endometrioma prior to IVF is only feasible in UK if an adaptive rather than traditional study design is used; this would minimise resource wastage and complete the trial in an acceptable time frame. https://www.selleckchem.com/products/wnt-agonist-1.html What is known already There is wide variation in the management of endometriomas prior to IVF, with decisions about treatment being influenced by personal preferences. Study design size and duration This was a mixed-methods study consisting of an online survey of clinicians, a focus group and individual interviews with potential trial participants. Participants/materials setting methods Endometriosis and fertility experts across the UK were invited to participate in an online anonymised questionnaire. Potential future trial participants were recruited from aproach for randomised trials is not feasible. Study funding/competing interests Funding was received from the NHS Grampian R&amp;D pump priming fund (RG14437-12). S.B. is Editor-in-Chief of HROPEN, and A.W.H. is Deputy Editor of HROPEN. Neither was involved in the review of this manuscript. L.S. reports grants from CSO and NIHR to do endometriosis research, outside the submitted work. K.C. reports grants from NIHR/HTA and CSO during the conduct of the study. J.H.e., A.W.H., J.D., S.B.r., K.B., G.B., J.H.u. and K.G. report no conflict of interest.Precision Medicine implies a deep understanding of inter-individual differences in health and disease that are due to genetic and environmental factors. To acquire such understanding there is a need for the implementation of different types of technologies based on artificial intelligence (AI) that enable the identification of biomedically relevant patterns, facilitating progress towards individually tailored preventative and therapeutic interventions. Despite the significant scientific advances achieved so far, most of the currently used biomedical AI technologies do not account for bias detection. Furthermore, the design of the majority of algorithms ignore the sex and gender dimension and its contribution to health and disease differences among individuals. Failure in accounting for these differences will generate sub-optimal results and produce mistakes as well as discriminatory outcomes. In this review we examine the current sex and gender gaps in a subset of biomedical technologies used in relation to Precision Medicine. In addition, we provide recommendations to optimize their utilization to improve the global health and disease landscape and decrease inequalities.Digital health metrics promise to advance the understanding of impaired body functions, for example in neurological disorders. However, their clinical integration is challenged by an insufficient validation of the many existing and often abstract metrics. Here, we propose a data-driven framework to select and validate a clinically relevant core set of digital health metrics extracted from a technology-aided assessment. As an exemplary use-case, the framework is applied to the Virtual Peg Insertion Test (VPIT), a technology-aided assessment of upper limb sensorimotor impairments. The framework builds on a use-case-specific pathophysiological motivation of metrics, models demographic confounds, and evaluates the most important clinimetric properties (discriminant validity, structural validity, reliability, measurement error, learning effects). Applied to 77 metrics of the VPIT collected from 120 neurologically intact and 89 affected individuals, the framework allowed selecting 10 clinically relevant core metrics.